Vision-based gait impairment analysis for aided diagnosis

Gait is a firsthand reflection of health condition. This belief has inspired recent research efforts to automate the analysis of pathological gait, in order to assist physicians in decision-making. However, most of these efforts rely on gait descriptions which are difficult to understand by humans, or on sensing technologies hardly available in ambulatory services. This paper proposes a number of semantic and normalized gait features computed from a single video acquired by a low-cost sensor. Far from being conventional spatio-temporal descriptors, features are aimed at quantifying gait impairment, such as gait asymmetry from several perspectives or falling risk. They were designed to be invariant to frame rate and image size, allowing cross-platform comparisons. Experiments were formulated in terms of two databases. A well-known generalpurpose gait dataset is used to establish normal references for features, while a new database, introduced in this work, provides samples under eight different walking styles: one normal and seven impaired patterns. A number of statistical studies were carried out to prove the sensitivity of features at measuring the expected pathologies, providing enough evidence about their accuracy

Gait recognition from corrupted silhouettes: a robust statistical approach

This paper introduces a method based on robust statistics to build reliable gait signatures from averaging silhouette descriptions, mainly when gait sequences are affected by severe and persistent defects. The term robust refers to the ability of reducing the impact of silhouette defects (outliers) on the average gait pattern, while taking advantage of clean silhouette regions. An extensive experimental framework was defined based on injecting three types of realistic defects (salt and pepper noise, static occlusion, and dynamic occlusion) to clean gait sequences, both separately in an easy setting and jointly in a hard setting. The robust approach was compared against two other operation modes: (1) simple mean (weak baseline) and (2) defect exclusion (strong benchmark). Three gait representation methods based on silhouette averaging were used: Gait Energy Image (GEI), Gradient Histogram Energy Image (GHEI), and the joint use of GEI and HOG descriptors. Quality of gait signatures was assessed by their discriminant power in a large number of gait recognition tasks. Nonparametric statistical tests were applied on recognition results, searching for significant differences between operation modes.This work has been supported by the grants P1-1B2012-22 and PREDOC/2012/05 from Universitat Jaume I, PROMETEOII/2014/062 from Generalitat Valenciana, and TIN2013-46522-P from Spanish Ministry of Economy and Competitiveness

Análisis automático del patrón de la marcha mediante visión por computador: problemas, métodos y aplicaciones

Automatic gait recognition has become a research topic of interest due to its advantages versus other biometrics. However, the procedure for its analysis is still an open issue. Firstly, in this thesis, a method to construct robust gait representations from corrupted source data (e.g. affected by persistent occlusions or heavy noise) is proposed. In another research line, methodologies for accurate gait-based enrollment and duplicate detection are thoroughly studied. Finally, two contributions to computer vision aided diagnosis are also presented. On the one hand, a new database simulating gait disorders as those caused by neurological diseases is introduced. On the other hand, a number of human-friendly features are proposed to reliably characterize these pathological patterns.El interés por el reconocimiento automático del patrón de la marcha ha aumentado notablemente en los últimos años debido a las ventajas que puede ofrecer con respecto a otras características biométricas. Sin embargo, el procedimiento para su análisis sigue siendo un objeto de estudio en todas sus fases. En esta tesis se propone, en primer lugar, un método para la construcción de representaciones robustas del patrón de la marcha a partir de información defectuosa, afectada por factores como ruido u oclusiones persistentes. Por otra parte, se definen metodologías para realizar tareas de enrolado automático y detección de duplicados a partir de muestras biométricas de personas caminando, acompañadas de una extensa y variada experimentación. Finalmente, se incluyen dos aportaciones a la ayuda al diagnóstico médico mediante el análisis de la forma de andar: una base de datos en la que se reproducen anomalías de la marcha inspiradas en trastornos neurológicos reales; y una serie de medidas que describen de forma precisa estos patrones patológicos

Aproximación práctica a la identificación biométrica a través del análisis de la forma de andar

Treball de final de Màster en Sistemes Intel·ligents. Curs 2011/2012Con este trabajo se pretende realizar una aproximación a la identi cación biométrica de personas a partir de su forma de andar, en condiciones similares a las de un escenario real. Cuando entre estas condiciones concurren requisitos de tiempo real, un aspecto crucial es detectar el primer instante de tiempo en que se dispone de cantidad su ciente de información para obtener decisiones ables. Así, se ha planteado estudiar cómo la efectividad del proceso de reconocimiento depende de la longitud de la secuencia de vídeo de la persona caminando. Para ello, se ha propuesto el cálculo incremental de una representación muy conocida de la forma de andar, GEI (Gait Energy Image), de forma que se disponga de descripciones periódicas actualizadas de este movimiento. El objetivo es determinar qué porción de una secuencia de vídeo podría ser su ciente para obtener una representación lo bastante discriminante que conduzca a tasas de reconocimiento biométrico similares a las que se obtendrían con la información de toda la secuencia. El estudio se ha validado mediante experimentos con colecciones de vídeos grabadas en entornos interiores y exteriores, que además incluyen diversos factores que afectan la forma de andar y por lo tanto di cultan su reconocimiento, como variaciones en el calzado, ropa, carga, etc